Method and system for determining a pose of camera

ABSTRACT

The invention is related to a method and system for determining a pose of a first camera, comprising providing or receiving a spatial relationship (Rvc  1 ) between a visual content displayed on a display device and the first camera, receiving image information associated with an image (B 1 ) of at least part of the displayed visual content captured by a second camera, and determining a pose of the first camera according to the image information associated with the image (B 1 ) and the spatial relationship (Rvc 1 ).

BACKGROUND

The present disclosure is related to a method and system for determininga pose of a camera.

SUMMARY

Camera pose estimation is a common and challenging task in manyapplications or fields, such as robotic navigation, 3D objectreconstruction, augmented reality visualization, etc. As an example, itis known that systems and applications, such as augmented reality (AR)systems and applications, could enhance information of a realenvironment by providing a visualization of overlayingcomputer-generated virtual information with a view of the realenvironment. The virtual information can be any type of visuallyperceivable data such as objects, texts, drawings, videos, or theircombination. The view of the real environment could be perceived asvisual impressions by user's eyes and/or be acquired as one or moreimages captured by a camera held by a user or attached on a device heldby a user.

A task of camera pose estimation is to compute a spatial relationship ora transformation between a camera and a reference object (orenvironment). Camera motion estimation is to compute a spatialrelationship or a transformation between a camera at one position andthe camera at another position. Camera motion is also known as camerapose which describes a pose of a camera at one position relative to thesame camera at another position. Camera pose or motion estimation isalso known as tracking a camera. The spatial relationship ortransformation describes a translation, a rotation, or their combinationin 3D space.

Vision based methods are known as being the most robust and popularmethods for computing a camera pose or motion. The vision based methodscompute a pose (or motion) of a camera relative to an environment basedon one or more images of the environment captured by the camera.However, such vision based methods are relying on the captured imagesand require detectable visual features in the images. Moreover, poorlight conditions and/or textureless environment could make the visionbased methods unreliable and robustless. Further, the vision basedmethods often require a known geometry of at least part of the realenvironment in order to determine a scale factor for the computed poseor motion. A correct scale factor defines true camera poses as they arein the real world. However, the known geometry is not often available.

Currently, location sensors, such as GPS or rotation sensors, such asgyroscopes, are used to initialize the vision based pose estimation.However, location sensors, such as GPS, are often inaccurate andimprecise, especially in an indoor environment.

Thus, there is a desire to provide a robust method to determine a camerapose relative to a reference object or environment with a correct scalefactor. For example, computer vision (CV) based SimultaneousLocalization and Mapping (SLAM), as disclosed in Davison, Andrew J., etal. “MonoSLAM: Real-time single camera SLAM.” Pattern Analysis andMachine Intelligence, IEEE Transactions on 29.6 (2007): 1052-1067, is awell-known technology for determining the position and/or orientation ofa camera relative to a real environment and creating a geometrical modelof the real environment without requiring any pre-knowledge of theenvironment. The creation of the model of the environment is also calledthe reconstruction of the environment.

SLAM systems have to be initialized by at least two images of the realenvironment acquired from a distinct movement of the camera.Furthermore, a single camera does not measure metric scale. Recoveredcamera poses and the model of the environment are up to a scale as anundetermined factor, see Strasdat, Hauke, J. M. M. Montiel, and AndrewJ. Davison. “Scale drift-aware large scale monocular SLAM.” Proceedingsof Robotics: Science and Systems (RSS). Vol. 2. No. 3. 2010. A correctscale factor defines true camera poses and the size of the reconstructedenvironmental model as they are in the real world.

Davison et al., in Davison, Andrew J., et al. “MonoSLAM: Real-timesingle camera SLAM.” Pattern Analysis and Machine Intelligence, IEEETransactions on 29.6 (2007): 1052-1067, propose to introduce calibrationobjects with known geo-metrical dimension for determining correct scalefactors for SLAM systems.

Lemaire at al. in Lemaire, Thomas, et al. “Vision-based slam: Stereo andmonocular approaches.” International Journal of Computer Vision 74.3(2007): 343-364 propose to use a stereo camera system to solve theproblem of determining scale factors in SLAM systems. However, using astereo camera is only a partial remedy, since the displacement betweenthe two cameras has to be significant in relation to the distance to theenvironment in order to reliably compute depth of the environment.

Lieberknecht et al., in Lieberknecht, Sebastian, et al. “RGB-Dcamera-based parallel tracking and meshing.” Mixed and Augmented Reality(ISMAR), 2011 10th IEEE International Symposium on. IEEE, 2011,integrate depth information into monocular vision based SLAM to allowcorrectly scaled camera pose estimation by employing a RGB-D camera thatprovides depth information related to image pixels. It is possible todetermine a scale factor from known depth information. However, a RGB-Dcamera device is not commonly available in a hand-held device, e.g.mobile phone, PDA, compared to a normal RGB camera.

In addition to SLAM, various vision based methods for camera poseestimation have been developed, such as using visual markers. Pustka etal., in Pustka, Daniel, et al. “Spatial relationship patterns: Elementsof reusable tracking and calibration systems.” ISMAR 2006, attachphysical spherical markers to a camera and determine poses or motions ofthe camera by using other cameras to detect the spherical markers'positions.

Grossmann et al., in U.S. Publication No. 2012/0287287 A, disclosedetermining a camera position relative to a display device according toimages of visual contents displayed on the display device captured bythe camera.

Osman, in PCT Publication No. WO 2011/075226 A1, proposes a method forlocating a camera of a gaming console relative to a display device. Hediscloses determining a camera position relative to a display device byanalyzing images of visual contents displayed on the display devicecaptured by the camera.

It is an object of the invention to provide a robust method to determinea camera pose relative to a reference object.

According to an aspect, there is provided a method for determining apose of a first camera, comprising providing or receiving a spatialrelationship between a visual content displayed on a display device andthe first camera, receiving image information associated with an imageof at least part of the displayed visual content captured by a secondcamera, and determining a pose of the first camera according to theimage information associated with the image and the spatialrelationship.

According to another aspect, there is provided a system for determininga pose of a first camera, comprising a processing device configured toprovide or receive a spatial relationship between a visual contentdisplayed on a display device and the first camera, wherein theprocessing device is configured to receive image information associatedwith an image of at least part of the displayed visual content capturedby a second camera, and the processing device is configured to determinea pose of the first camera according to the image information associatedwith the image and the spatial relationship.

The present invention proposes to determine a pose or a motion of afirst camera by using a second camera to capture one or more images of avisual content displayed on a display device that has a known or fixedspatial relationship with the first camera.

The first camera could be fixed or have a known position with respect tothe display device. For example, the display device and the first cameracould be attached to a mobile device (e.g. a mobile phone or a tabletcomputer) at fixed or known positions. Visual contents displayed on thedisplay device could be textured. Further the displayed visual contentsmay have known sizes, e.g. obtained from their resolutions. It ispossible and robust to determine a pose or motion of the first camera byusing the second camera to capture images of a visual content displayedon the display device. Further, if the second camera is at substantiallythe same position with respect to an environment, e.g. the earth or anin-door environment, while the first camera moves with respect to theenvironment, the present invention could also be used to robustlyestimate a motion of the first camera in the environment. The firstcamera may further acquire images of the environment. The estimatedmotion of the first camera and image information associated with theimages (such as raw image data or processed image data) captured by thefirst camera can be used to reconstruct at least part of the environmentor to initialize a simultaneous localization and mapping (SLAM) system.

According to an embodiment, the first camera and the display device arephysically connected.

For example, the first camera is at a fixed position with respect to thedisplay device after the spatial relationship is provided.

Preferably, the first camera and the display device are comprised in amobile device. A mobile computing device, such as a mobile phone, atablet computer, or a laptop computer, nowadays often comprises a cameraand a display device. Typically, the camera and the display device havefixed or known positions relative to the mobile device.

According to an embodiment, the method further comprises determining apose of the second camera relative to the displayed visual contentaccording to the image.

According to an embodiment, the displayed visual content has a knownvisual appearance.

For example, the spatial relationship between the displayed visualcontent and the first camera is determined by a calibration procedure,for example by a hand-eye calibration.

According to an embodiment, the pose of the first camera is a pose ofthe first camera relative to the second camera, and wherein thedetermining the pose of the first camera comprises determining a pose ofthe second camera relative to the displayed visual content according tothe image information associated with the image.

According to an embodiment, the method further comprises receiving imageinformation associated with a first image of at least part of a realenvironment captured by the first camera at the pose relative to thesecond camera, wherein the image of at least part of the displayedvisual content captures the at least part of the real environment, andreconstructing a model of the at least part of the real environmentaccording to the image information associated with the image of at leastpart of the displayed visual content and the first image, and the pose.

According to another embodiment, the method further comprises receivingimage information associated with a first image of at least part of areal environment captured by the first camera at the pose relative tothe second camera, wherein the pose is a first pose, receiving imageinformation associated with a second image of the at least part of thereal environment captured by the first camera at a second pose relativeto the second camera, and reconstructing a model of the at least part ofthe real environment according to the image information associated withthe first and second images and the first and second poses.

For example, the method may further comprise receiving image informationassociated with a further image of at least part of the displayed visualcontent captured by the second camera while the first camera is at thesecond pose relative to the second camera, and determining the secondpose of the first camera relative to the second camera according to theimage information associated with the further image and the spatialrelationship between the displayed visual content and the first camera.

According to another embodiment of the method, in which the pose of thefirst camera is relative to a real object, the determining the pose ofthe first camera comprises receiving image information associated withan image of at least part of the real object captured by the secondcamera, determining a homography according to image positions of the atleast part of the displayed visual content in the image of at least partof the displayed visual content and image positions of the at least partof the real object in the image of at least part of the real object,wherein the at least part of the displayed visual content is planar andthe at least part of the real object is planar, and determining the poseof the first camera relative to the real object according to thehomography and the spatial relationship.

According to an embodiment, the image of at least part of the displayedvisual content and the image of at least part of the real object are thesame image or different images, and wherein the visual content is afirst visual content, the display device is a first display device, andthe real object is a second visual content displayed on a second displaydevice.

According to another embodiment of the method, in which the pose of thefirst camera is a pose of the first camera at a first position while theimage is captured relative to the first camera at a second position, thedetermining the pose of the first camera comprises receiving imageinformation associated with a further image of at least part of thedisplayed visual content captured by the second camera while the firstcamera is at the second position, determining a homography according toimage positions of the at least part of the displayed visual content inthe image and in the further image, wherein the at least part of thedisplayed visual content is planar, and determining the pose of thefirst camera according to the homography and the spatial relationship.

For example, the method may further comprise receiving image informationassociated with a first image of at least part of a real environmentcaptured by the first camera at the first position, receiving imageinformation associated with a second image of at least part of the realenvironment captured by the first camera at the second position, andreconstructing a model of the at least part of the real environmentaccording to the image information associated with the first and secondimages and the pose of the first camera.

Regarding the system for determining a pose of a first camera, accordingto an embodiment, the processing device may be comprised in a mobiledevice which comprises the first camera. For example, the method may beimplemented as an application which runs on the processing device of amobile device, such as a mobile phone, comprising the first camera andthe display device, and which communicates with a device, such as a headmounted display, comprising the second camera (e.g. attached to the headmounted display).

According to another embodiment, the processing device is comprised in amobile device which comprises the second camera. For example, the methodmay be implemented as an application which runs on the processing deviceof a mobile device, such as a head mounted display, comprising thesecond camera, and which communicates with a mobile device, such as amobile phone, comprising the first camera and the display device.

According to another embodiment, the processing device is comprised in acomputer device which communicates with a first mobile device comprisingthe first camera and with a second mobile device comprising the secondcamera. For example, the method may be implemented as an applicationwhich runs on the processing device of a computer, such as a mobilecomputer or a personal computer, communicating with a mobile device,such as a head mounted display, comprising the second camera and with amobile device, such as a mobile phone, comprising the first camera andthe display device.

For example, the mobile device comprising the first camera is a handheld device, such as a mobile phone, a tablet computer or a mobilecomputer. According to an embodiment, the second camera is comprised ina mobile device, such a head mounted display device.

According to another aspect, the invention is also related to a computerprogram product comprising software code sections which are adapted toperform a method according to the invention when loaded into theinternal memory of a processing device. Particularly, the computerprogram product is contained on a computer readable medium and isnon-transitory. The software code sections may be loaded into a memoryof one or more of the processing devices as described herein.

The display device is a device for presentation of information invisual, i.e. visual contents. The display device could be based on anydisplaying technologies or materials, such as Cathode ray tube (CRT),light-emitting diode display (LED) and liquid crystal display (LCD). Thedisplay may be a 2-dimensional planar display or a display having acurved shape. The display may also be a foldable display consisting ofmultiple planar sub-displays, each of which could be moveable withothers.

The visual content is any visually perceivable information to anatomicaleyes or optical imaging devices. For example, the visual content mayemit or reflect visible light that could be captured by human eyes orcameras. The visual content may also emit or reflect invisible lightthat could not be captured by human eyes, but could be captured by acamera. For example, the visual content may be an infrared figure andcan be captured by an infrared camera. The visual content could be text,one or more figures, one or more images generated by computers orcaptured by cameras, symbols, drawings, or any combinations thereof. Thevisual content can be displayed on the display device.

The first camera and the second camera are optical imaging devices thatcould capture imagery information of optical information.

The proposed invention can be employed with any type of camera providingimages. It is not restricted to cameras providing color images in theRGB format. It can also be applied to any other color format and also tomonochrome images, for example to cameras providing images in grayscaleformat. The first and/or second camera may further provide an image withdepth data. The depth data does not need to be provided in the sameresolution as the (color/grayscale) image. A camera providing an imagewith depth data is often called RGB-D camera. A RGB-D camera systemcould be a time of flight (TOF) camera system. The camera may alsocapture light that is invisible to human eye, such as infrared light.For example, the first and/or second camera may be a thermal imagingcamera.

Particularly, a visual appearance of the displayed visual contentdescribes shape, texture, or their combinations. The visual appearancemay or may not include color information.

A physical geometry of an object describes size, shape, dimension,and/or planarity, or their combinations for the object in the realworld.

A resolution of the display device is the number of distinct pixels ineach dimension that can be displayed on its display area. The displaydevice may have a known resolution. The display device may further havea known physical geometry for its display area. The physical geometry ofthe display device refers to the physical geometry for the display areaof the display device. For example, having a pixel position of thedisplayed visual content in a coordinate system of the display device,and the resolution and the physical geometry of the display device, aspatial relationship between the displayed visual content and thedisplay device can be determined. Further, a physical geometry of thedisplayed visual content can also be determined.

According to another embodiment, having the visual appearance of thedisplayed visual content and the physical geometry of the displaydevice, the spatial relationship between the displayed visual contentand the display device could also be determined according to an imagecapturing, both, the displayed visual content and the display devicewithout knowing the resolution of the display device and the pixelposition of the displayed visual content. This relies on an assumptionthat the visual content is displayed on the top surface of the displaydevice. For example, if the display device is planar, the displayedvisual content locates on the same plane as the display device in 3Dspace. Various computer vision and image processing methods can beapplied to first determine the 3D position of the planar display deviceaccording to the physical geometry of the display device. The 3Dposition of the plane of the display device also defines a plane wherethe display visual content locates. Then, having the plane informationand the captured image, the physical geometry of the displayed visualcontent and the spatial relationship between the displayed visualcontent and the display device can be determined.

A spatial relationship between the first camera and the display devicemay be known. The spatial relationship between the first camera and thedisplay device could also be calibrated by a calibration procedure, suchas a hand-eye calibration, see for example Horaud, Radu, and FadiDornaika. “Hand-eye calibration.” The international journal of roboticsresearch 14.3 (1995): 195-210. The first camera should be at asubstantially fixed position with respect to the display device duringand after the calibration. If the first camera moves with respect to thedisplay device, the spatial relationship may have to be re-calibratedagain, unless the movement is known or determined. The first camera maybe preferred to be fixed relative to the display device after thecalibration.

The spatial relationship between the displayed visual content and thefirst camera may be known or determined according to the spatialrelationship between the displayed visual content and the display deviceand the spatial relationship between the first camera and the displaydevice.

The spatial relationship between the displayed visual content and thefirst camera could also be determined by a calibration procedure, suchas a hand-eye calibration. This requires that the visual content isdisplayed on the display device while the calibration procedure isconducted.

The first camera and the display device are preferred to be physicallyconnected. The first camera is preferably at a fixed position withrespect to the display device after determining or providing the spatialrelationship between the displayed visual content and the first camera.

The pose of the first camera to be determined may be a pose of the firstcamera relative to the second camera. A pose of the second camerarelative to the displayed visual content may be determined according toan image of at least part of displayed visual content captured by thesecond camera. The pose of the first camera relative to the secondcamera may be determined according to the determined pose of the secondcamera and the spatial relationship between the displayed visual contentand the first camera.

The pose of the first camera to be determined may be a pose of the firstcamera relative to a real object. At least part of the displayed visualcontent and at least part of the real object may be captured by oneimage using the second camera. The at least part of the displayed visualcontent and the at least part of the real object may also be captured bytwo images respectively using the second camera. When the at least partof the displayed visual content and the at least part of the real objectare planar, a planar homography may be estimated according to imagepositions of the at least part of the displayed visual content and theat least part of the real object, like proposed in Agarwal, Anubhav, C.V. Jawahar, and P. J. Narayanan. “A survey of planar homographyestimation techniques.” Centre for Visual Information Technology, Tech.Rep. IIIT/TR/2005/12 (2005). A pose of the displayed visual contentrelative to the real object may be determined according to the estimatedplanar homography by a homography decomposition method, like proposed inMalis, Ezio, and Manuel Vargas. “Deeper understanding of the homographydecomposition for vision-based control.” (2007). APA. The pose of thefirst camera relative to the real object may be determined according tothe pose of the displayed visual content relative to the real object andthe spatial relationship between the displayed visual content and thefirst camera. The at least part of the real object may also includeanother visual content displayed on another display device.

The pose of the first camera to be determined may be a pose of the firstcamera at a first position relative to the same first camera at a secondposition. The first position and the second position are differentpositions in a coordinate system of the second camera. A first image ofat least part of the displayed visual content may be captured by thesecond camera while the first camera is at the first position. A secondimage of the at least part of the displayed visual content may becaptured by the second camera while the first camera is at the secondposition. When the at least part of the displayed visual content isplanar, a planar homography may be estimated according to imagepositions of the at least part of the displayed visual content in thefirst and second images, like proposed in Agarwal, Anubhav, C. V.Jawahar, and P. J. Narayanan. “A survey of planar homography estimationtechniques.” Centre for Visual Information Technology, Tech. Rep.IIIT/TR/2005/12 (2005). A spatial relationship between the visualcontent displayed on the display device connected to the first camerawhile the first camera is at the first position and at the secondposition may be determined according to the estimated planar homographyby a homography decomposition method, like proposed in Malis, Ezio, andManuel Vargas. “Deeper understanding of the homography decomposition forvision-based control.” (2007). APA. The pose of the first camera at thefirst position relative to the same first camera at the second positionmay be determined according to the spatial relationship between thevisual content and the spatial relationship between the displayed visualcontent and the first camera.

In another example, the first camera at the second position may beanother camera connected with another display device that is differentfrom the first camera and the display device connected to the firstcamera. The another display device may display another visual contentthat is different from the visual content displayed on the displaydevice connected to the first camera. At least part of the displayedvisual content and at least part of the another displayed visual contentmay be captured by one image or captured respectively by two imagesusing the second camera. The pose of the first camera at the firstposition relative to the another camera at the second position may bedetermined according to the same method disclosed above.

The system for determining a pose of a first camera has at least oneprocessing device, such as a microprocessor, such as provided in amobile phone, a tablet computer, a laptop, or a desktop PC. Thedetermination or estimation of camera poses, camera motions, and modelsof at least part of a real environment may be performed by suchprocessing device.

In one embodiment, the system for determining the pose of the firstcamera may be a mobile device and further comprise the first camera andthe display device attached to the mobile device. The first camera ispreferred to be at a fixed position relative to the display device inthe system. A spatial relationship between the first camera and thedisplay device attached to the system may be known or calibrated by acalibration procedure, such as hand-eye calibration.

The system for determining the pose of the first camera may be separatefrom the second camera. The system could receive from the second camera,or from a device communicating with the second camera, image informationassociated with images captured by the second camera and/or cameraintrinsic parameters. The system may communicate with the second cameraor device via a cable, wirelessly or via a computer network.

In another embodiment, the system for determining the pose of the firstcamera comprises the second camera and is separate from the first cameraand the display device. In this embodiment, the system could receiveinformation (e.g. visual appearance) related to the visual contentand/or to the display device from the display device and further receiveimage information associated with images captured by the first cameraand/or camera intrinsic parameters from the first camera via a cable,wirelessly or via a computer network.

In another embodiment, the system for determining the pose of the firstcamera may be separate from the first camera, the display device, andthe second camera. In this case, the system could receive information(e.g. visual appearance) related to the visual content and/or to thedisplay device from the display device, receive image informationassociated with images captured by the second camera and/or cameraintrinsic parameters from the second camera, and further receive imageinformation associated with images captured by the first camera and/orcamera intrinsic parameters from the first camera via a cable,wirelessly or via a computer network.

The computer network may be a telecommunications network that connectsdevices (e.g. computers) to allow communication and data exchangebetween systems, software applications, and users. The computers may beconnected via cables, or wireless, or both of cables and wireless. Forexample, the computer network could be an Internet, intranet, local areanetwork, or wide area network.

DESCRIPTION OF THE DRAWINGS

Aspects and embodiments of the invention will now be described withrespect to the drawings, in which:

FIG. 1a shows a flowchart of determining a pose of a first camera of amobile phone using a second camera according to an embodiment of theinvention,

FIG. 1b shows a flowchart of determining a pose of a first camera of amobile phone using a second camera according to another embodiment ofthe invention,

FIG. 1c shows a flowchart of determining a pose of a first camera of amobile phone using a second camera according to a further embodiment ofthe invention,

FIG. 2 shows an illustration of an exemplary arrangement of componentsaccording to an embodiment of the invention.

DETAILED DESCRIPTION

According to a possible implementation, an exemplary application of thepresent invention is to determine a pose of a first camera of a mobilephone using a second camera, wherein the mobile phone further comprisesa display device. Although various embodiments are described in thefollowing with reference to components as shown in FIG. 2, any otherconfiguration of components, as described herein, can also be used whenimplementing any of these embodiments.

FIG. 2 shows an illustration of an exemplary arrangement of componentsaccording to an embodiment of the invention in a scenario of tracking acamera 2004 (first camera) that is attached to a mobile device, here ahand-held device (HHD) 2001, such as a mobile phone, equipped with adisplay device 2002, such as a screen or touchscreen. The tracking ofthe camera 2004 uses a camera 2008 (second camera) attached to anothermobile device, here a head-mounted device (HMD) 2007 which may compriseglasses for providing so-called video-see-through or optical-see-throughto a real environment to a user wearing the glasses.

The HHD 2001 has at least one processing device, such as amicroprocessor and associated circuitry which are commonly used in theart and not shown in the Figures, since they are internal to the HHD.The internal processing device is indicated with reference number 2011in FIG. 2. Among other tasks as commonly used and applied in the art,with regard to the present invention the processing device 2011 isconfigured to display images, such as visual content, on the displaydevice 2002. The processing device 2011 is further applicable to performtasks and steps as described herein in connection with the invention,such as the steps as described with reference to FIG. 1a , FIG. 1b , orFIG. 1 c.

The display device 2002 has a planar displaying area, such as a screen,with a known physical size. In this example, the HHD 2001 may be held bya user and the HMD 2007 is worn at the head of the same or a differentuser. Camera intrinsic parameters of the camera 2004 and the camera 2008are provided or determined by a camera calibration procedure.

In this example, the HMD 2007 comprises a semi-transparent display (orsemi-transparent glasses) 2010 such that the user sees through thesemi-transparent glasses one or more objects of the real environmentaugmented with computer-generated visual objects blended in on theglasses.

The HMD 2007 has at least one processing device 2012, such as amicroprocessor and associated circuitry which are commonly used in theart. Among other tasks as commonly used and applied in the art, withregard to the present invention the processing device 2012 is configuredto display visual content on the display 2010. The processing device2012 is further applicable to perform tasks and steps as describedherein in connection with the invention, such as the steps as describedwith reference to FIG. 1a , FIG. 1b , or FIG. 1 c.

According to an embodiment, each of the processing devices 2011 and/or2012 is appropriate and may be configured to provide or receive spatialrelationships as described herein, to receive image informationassociated with images captured by the first camera 2004 and/or secondcamera 2008 directly from the respective camera or from anotherprocessing device, and to determine poses of the first camera 2004relative to the second camera 2008 according to received imageinformation and one or more of the spatial relationships, as describedin detail herein. These tasks may also be performed by anotherprocessing device, such as processing device 3001, which is neithercontained in the HHD 2001 nor in the HMD 2007, but in another device3000, such as a mobile computer, communicating with the HHD 2001 and HMD2007, e.g. wirelessly. Further, it is possible that all or some of thetasks and steps as described herein may be shared or distributed betweenthe processing devices 2011, 2012 and 3001.

The HHD 2001 and the HMD 2007 may communicate with each otherwirelessly. The camera 2004 and the display device 2002 have fixedpositions on the HHD 2001. Thus, the camera 2004 is fixed relative tothe display device 2002. A spatial relationship Re ld between the camera2004 and the display device 2002 is provided by the manufacturer of theHHD 2001. The spatial relationship Rc1 d can also be determined byhand-eye calibration. For example, move the HHD 2001 while estimating amotion Mel of the camera 2004 and a motion Md of the display device2002. The spatial relationship Rc1 d can then be determined by ahand-eye calibration method (see Horaud, Radu, and Fadi Dornaika.“Hand-eye calibration.” The international journal of robotics research14.3 (1995): 195-210) according to the motions Mel and Md.

The motion Mel of the camera 2004 can be estimated by capturing imagesof a visual marker placed in a real environment. The motion Mel can bedetermined using various computer vision methods according to thecaptured images. The motion Md of the display device 2002 can beestimated by using the camera 2008 of the HMD 2007 to capture images ofthe display device 2002. Having a known geometric model of the displaydevice, computer vision methods can be used to determine Md according tothe captured images. The motion Md may also be estimated by using thecamera 2008 of the HMD 2007 to capture images of a visual contentdisplayed on the display device 2002. For this, a known visualappearance of the visual content and its position with respect to thedisplay device are required.

The hand-eye calibration of estimating the spatial relationship Rc1 dmay be performed on the HHD 2001 that receives from the HMD 2007 theimages of the displayed visual content captured by the camera 2008.

Similarly, a spatial relationship Rya between the camera 2004 and adisplayed visual content 2003 can also be estimated according to thehand-eye calibration method (see Horaud, Radu, and Fadi Dornaika.“Hand-eye calibration.” The international journal of robotics research14.3 (1995): 195-210). This requires estimating a motion Mm of thedisplayed visual content 2003 instead of the motion Md of the displaydevice 2002. The motion Mm may be estimated by using the camera 2008 ofthe HMD 2007 to capture images of the displayed visual content 2003.

The resolution of the display device 2002 is known. A visual content(here in the form of a square marker) 2003 is displayed at a known pixelposition on the display device 2002. The square marker 2003 also has aknown pixel size. The square marker could also be replaced by othervisual contents, such as menus, buttons, icons, and program userinterfaces of the mobile phone, displayed on the display device 2002.

FIG. 1 a shows a flowchart of determining a pose of the camera 2004(first camera) of the HHD 2001 using the camera 2008 (second camera) andfurther of reconstructing a model of a chair based on images captured bythe camera 2004.

In step 1001, as the HHD 2001 a mobile phone is provided comprising adisplay device 2002 and a first camera 2004. In step 1002, a squaremarker 2003 is displayed on the display device 2002 as a visual content.In step 1003, a spatial relationship Rc1 d between the display device2002 and the first camera 2004 is provided. The spatial relationship Rdd is often known from the mobile phone manufacturer. The spatialrelationship Rc1 d could also be calibrated, as described above. In step1004, a spatial relationship Rvd between the display device 2002 and thedisplayed square marker 2003 is determined. Then, a spatial relationshipRya between the first camera 2004 and the displayed square marker 2003is determined according to the spatial relationships Rc1 d and Rvd (step1005).

In step 1006, an image B 1 of the displayed square marker 2003 iscaptured by the second camera 2008 while the first camera 2004 locatesat a pose P1 relative to the second camera 2008. In step 1007, a pose K1 of the second camera 2008 relative to the displayed square marker 2003is determined according to the image Bl. Instep 1008, the pose P1 of thefirst camera 2004 relative to the second camera 2008 is determinedaccording to the pose K 1 and the spatial relationship Rvc1. In step1009, an image A1 of a chair, such as chair 2009 in FIG. 2, is capturedby the first camera 2004 at the pose P1. Then, the HHD 2001 is moved toanother location such that the first camera 2004 locates at a pose P2relative to the second camera 2008 in step 1010. In step 1011, an imageA2 of the chair is captured by the first camera 2004 and an image B2 ofthe displayed square marker is captured by the second camera 2008 whilethe first camera 2004 is at the pose P2. In step 1012, the pose P2 isdetermined according to the spatial relationship Rvc1 and the image B2.Thereafter, a model of the chair 2009 may be reconstructed according tothe images A1 and A2 and the poses P1 and P2 in step 1013.

The spatial relationship Rvd between the displayed square marker 2003and the display device 2002 may be determined as follows: Having aresolution of the display device 2002, the physical size of thedisplaying area of the display device 2002, the pixel position and pixelsize of the square marker 2003, the physical size of the displayedsquare marker 2003 and its spatial relationship Rvd with respect to thedisplay device 2002 can be determined. This step could be performed onthe HHD 2001.

The spatial relationship Rvc1 between the displayed square marker 2003and the camera 2004 is determined according to the spatial relationshipRvd and the spatial relationship Rd d.

The camera 2008 captures an image B1 of the displayed square marker2003. A pose K1 of the camera 2008 relative to the displayed squaremarker 2003 is determined according to the image B 1 by using computervision methods, such as in Sanni Siltanen, Theory and applications ofmarker-based augmented reality. Espoo 2012. VTT Science 3.http://www.vtt.fi/inf/pdf/science/2012/83.pdf. The determination of thepose K1 is performed on the HHD 2001 that receives from the HMD 2007 theimage B 1. This could also be performed on the HMD 2007.

Generally, the computer vision methods used to determine the pose K1 canload what is shown on the display device 2002 as a target image or areference image to initialize the determination of the pose K1.

A pose P1 (the location of which is indicated by 2005 in FIG. 2) of thecamera 2004 relative to the camera 2008 can be computed according to thepose K 1 and the spatial relationship Rvc1. At the pose P1, the camera2004 captures image A1 of the chair 2009 located in a room.

The user could move the HHD 2001 to another location 2006 and use thecamera 2004 to capture an image A2 of the chair 2009 at a pose P2relative to the second camera 2008. The pose P2 can be determined in thesame manner as with determining the pose P1.

If the user does not move the head (i.e. the camera 2008 of the HMD2007) with respect to the chair 2009 when the camera 2004 is placed atthe poses P1 and P2, a model of the chair 2009 can be reconstructedbased on a triangulation method (see, e.g., Hartley, Richard, and AndrewZisserman. Multiple view geometry in computer vision. Vol. 2. Cambridge,2000) using the images A1 and A2 and the poses P1 and P2. Thereconstructed model of the chair will have a correct scale factor.

The pose K1 of the second camera 2008 relative to the displayed visualcontent 2003 can be determined according to the image B 1 of thedisplayed visual content captured by the second camera 2008. Having theknown visual appearance of the displayed visual content 2003 and itsphysical geometry, the pose K1 can be determined with a correct scalefactor. The pose estimation could be based on correspondences betweenimage features of the image B 1 and corresponding features of the visualcontent 2003 displayed on the display device 2002.

The pose P1 of the first camera 2004 relative to the second camera 2008can be determined according to the pose K 1 and the spatial relationshipRvc1.

The real environment could be an indoor office or an outdoor scene. Thereal environment could also be or include a real object, such as a sofa,a car, a human, a tree, and a building. The at least part of the realenvironment could be a part of the real environment and/or at least onereal object located in the real environment.

The image A2 of the at least part of the real environment may becaptured by the first camera 2004 while the first camera is at pose P2relative to the second camera 2008. The poses P1 and P2 are different.

The image B2 of at least part of the visual content (or another visualcontent) 2003 displayed on the display device 2002 could be captured bythe second camera 2008 while the first camera 2004 is at the pose P2relative to the second camera 2008.

A pose K2 of the second camera 2008 relative to the displayed visualcontent 2003 is determined according to the image B2. The pose P2 of thefirst camera 2004 relative to the second camera 2008 is determinedaccording to the pose K2 of the second camera 2008 relative to thevisual content 2003 and the spatial relationship Rvc1.

Further, if the second camera 2008 keeps unmoved relative to the atleast part of the real environment when the first camera 2004 locates atthe poses P1 and P2, it is possible to determine a motion of the firstcamera 2004 with respect to the at least part of the real environmentaccording to the poses P1 and P2. The determined motion could have acorrect scale factor.

If the second camera 2008 keeps unmoved relative to the at least part ofthe real environment when the first camera 2004 locates at the poses P1and P2, a model of the at least part of the real environment could bereconstructed according to the images A1 and A2 and the poses P1 and P2.In one example of reconstructing the model, correspondences betweenimage features of the at least part of the real environment in theimages A1 and A2 may be determined. Then, a triangulation method, likeproposed in Hartley, Richard, and Andrew Zisserman. Multiple viewgeometry in computer vision. Vol. 2. Cambridge, 2000, can be used todetermine the model from the image feature correspondences and the posesP1 and P2.

Further, if the display device 2002 keeps unmoved relative to the atleast part of the real environment when the second camera 2008 locatesat the poses K1 and K2 relative to the display device 2002, it ispossible to determine a motion of the second camera 2008 with respect tothe at least part of the real environment according to the poses K 1 andK2. The determined motion could have a correct scale factor. The motionof the second camera 2008 may also be determined according to imagepositions of the displayed visual content 2003 in the images B1 and B2.For example, a planar homography may be estimated based on the imagepositions of the displayed visual content 2003 in the images B1 and B2(see Agarwal, Anubhav, C. V. Jawahar, and P. J. Narayanan. “A survey ofplanar homography estimation techniques.” Centre for Visual InformationTechnology, Tech. Rep. IIIT/TR/2005/12 (2005)). The motion of the secondcamera 2008 may be determined according to homograph decomposition (seeMalis, Ezio, and Manuel Vargas. “Deeper understanding of the homographydecomposition for vision-based control.” (2007). APA). If the images B1and B2 capture same at least part of the real environment, a model ofthe at least part of the real environment could be reconstructedaccording to the images B1 and B2 and the poses K1 and K2 or accordingto the images B1 and B2 and the motion of the second camera 2008.

FIG. 1b shows another flowchart of determining a pose of the camera 2004(first camera) of the HHD 2001 using the camera 2008 (second camera) andfurther of reconstructing a model of a chair based on an image capturedby the camera 2004 and an image captured by the camera 2008.

Steps 1001, 1002, 1003, 1004, 1005, 1007, 1008 and 1009 in FIG. 1b arethe same as the ones in FIG. 1a that are described above. In step 1 b006, the second camera captures an image B1 of the displayed squaremarker and a chair. Image information related to the displayed visualmarker in the image B1 is used to determine the pose P1 of the firstcamera relative to the second camera. The pose P1 describes a spatialrelationship between the first camera and the second camera while theimage A1 is captured by the first camera and the image B1 is captured bythe second camera. In step 1 b 010, a model of the chair may bereconstructed according to the images A1 and B1 and the pose P1 based onthe triangulation method.

The camera 2004 and the camera 2008 could be synchronized such that itis possible to enable the camera 2004 to capture an image (e.g. theimage A1) and the camera 2008 to capture another image (e.g. the imageB1) at a same moment, and/or to relate an image captured by the camera2004 and another image captured the camera 2008 if the two images arecaptured at a same moment.

The camera 2004 and the display device 2002 of the device HHD 2001 maybe synchronized using the same internal processing device 2011. Thecamera 2004 and the camera 2008 may be synchronized by displaying aspecific visual content on the display device 2002 and detecting thespecific visual content in an image captured by the second camera 2008.For example, the internal processing device 2011 may control the camera2004 to capture the image A1 and control the display device 2002 todisplay the square marker 2003 only at the moment while the image A1 iscaptured. The camera 2008 continuously captures images of visualcontents displayed on the display device 2002. As soon as the squaremarker 2003 is detected in an image captured by camera 2008, this imageis used as the image B1. In this way, it is possible that the image A1and the image B1 are captured at the same moment.

The synchronization method mentioned above can also be applied tosynchronize processing steps executed on the HHD 2001 and executed onthe HMD 2007.

FIG. 1c shows another flowchart of determining a spatial relationshipbetween the camera 2004 (first camera) of the HHD 2001 at differentposes relative to the camera 2008 (second camera) and further ofreconstructing a model of a chair based on images captured by the camera2004.

Steps 1001, 1002, 1003, 1004, 1005, 1006, 1009, 1010 and 1011 in FIG. 1eare the same as the ones in FIG. 1a that are described above. Step 1 c012 determines the spatial relationship (i.e. pose M1) between the firstcamera 2004 at the pose P1 and at the pose P2 according to the images B1and B2. The pose M1 describes a pose of the first camera 2004 at a firstposition (pose P1) relative to the same first camera 2004 at a secondposition (pose P2). The pose Ml may also be called as camera motion forthe same first camera. The displayed visual content 2003 is planar, andthus a planar homography can be estimated based on image positions ofthe displayed visual content 2003 in the images B 1 and B2. The pose Mlcan be determined by decomposing the estimated planar homography using amethod, like proposed in Malis, Ezio, and Manuel Vargas. “Deeperunderstanding of the homography decomposition for vision-based control.”(2007). APA. In step 1 c 013, a model of the chair is reconstructedaccording to the images A1 and A2 and the pose M1.

In all examples described above, there is only one mobile device (heremobile phone), i.e. the HHD 2001. The HHD 2001 may locate at the twodifferent locations 2005 and 2006. It is obvious that the HHD 2001located at one of the locations 2005 and 2006 may be replaced by anothermobile device comprising another display device and another camera. Inthis case, the another display device of the another mobile device maydisplay another visual content different from the visual content 2003 inorder to distinguish the another mobile device from the HHD 2001.Further, the second camera may capture only one image that captures boththe visual content 2003 and the another visual content.

Generally, the reconstructed model at least describes the depthinformation of the at least part of the real environment. The model mayfurther include one of the following attributes, but not limited to:shape, symmetry, planarity, geometrical size, color, texture anddensity.

The reconstructed model of the at least part of the real environmentcould have a correct scale factor. The reconstructed model can berepresented as a model comprising 3D vertices and polygonal faces and/oredges spanned by these vertices. Edges and faces of the model may alsobe represented as splines or NURBS surfaces.

Furthermore, the reconstructed model can further be used to initialize avision based SLAM system for tracking the first camera in the realenvironment and/or reconstructing a model of other parts of the realenvironment. This does not need the second camera.

According to an embodiment, the HHD 2001 and the camera 2004 could betracked in the room using images captured by the camera 2004 based on aSLAM method (see, e.g., Davison, Andrew J., et al. “MonoSLAM: Real-timesingle camera SLAM.” Pattern Analysis and Machine Intelligence, IEEETransactions on 29.6 (2007): 1052-1067). The SLAM method is initializedby the reconstructed model of the real environment. The model of theinterior of the room can also be reconstructed based on the monocularSLAM method using the first camera 2004. This procedure does not needthe camera 2008 and the HMD 2007. Thus, the user could freely move hishead and walk in the room. This way is particularly beneficial to singlecamera based SLAM methods.

Similarly, the display device 2002 of the HHD 2001 could also be trackedin the room based on SLAM, as the camera 2004 and the display device2002 have a known spatial relationship. This does not need to displaythe visual marker 2003.

Placing a virtual object in a real environment such that people couldview the virtual object later using an augmented reality system is achallenging task.

The display device 2002 (i.e. the HHD 2001) could be used as a physicalrepresentative of the virtual object. In contrast to using otherphysical objects, the display device could display visual information,which makes the virtual object visible to the user. Particularly, for aplanar virtual object, such as a 2D image or a video, the display device2002 could display the planar virtual object. Thus, a user could placethe planar virtual object in the room in a very intuitive way by movingthe display device 2002 that is tracked in the room using the camera2008. However, a normal physical object that could easily be tracked,such a square marker, does not have this capability of displaying orvisualizing the virtual object.

Throughout this document it is described that image informationassociated with an image is provided or received. It is known to theskilled person that this may include providing or receiving anyprocessed or non-processed information (version) of an image, part of animage and/or features of an image which allows for pose estimation. Theinvention does not require providing or receiving any raw original imagedata. Processing thereby includes any one of compression (e.g. JPEG,PNG, ZIP), encryption (e.g. RSA encryption, Schnorr signature, El-Gamalencryption, PGP), conversion to another color space or gray-scale,cropping or scaling the image or conversion into a sparse representationbased on feature descriptors, extraction, and their combinations. Allthese image processing methods can optionally be performed and arecovered by the terminology of image information associated with animage.

1. A method for determining a pose of a first camera, comprising:obtaining a spatial relationship between a visual content displayed on adisplay device and the first camera, receiving image informationassociated with an image of at least part of the displayed visualcontent captured by a second camera and determining a pose of the firstcamera according to the image information associated with the image andthe spatial relationship.
 2. The method according to claim 1, whereinthe pose of the first camera is a pose of the first camera relative tothe second camera, and wherein the determining the pose of the firstcamera comprises determining a pose of the second camera relative to thedisplayed visual content according to the image information associatedwith the image.
 3. The method according to claim 2, further comprisingreceiving image information associated with a first image of at leastpart of a real environment captured by the first camera at the poserelative to the second camera, wherein the image of at least part of thedisplayed visual content captures the at least part of the realenvironment; and reconstructing a model of the at least part of the realenvironment according to the image information associated with the imageof at least part of the displayed visual content and the first image,and the pose.
 4. The method according to claim 2, further comprisingreceiving image information associated with a first image of at leastpart of a real environment captured by the first camera at the poserelative to the second camera, wherein the pose (P1) is a first pose;receiving image information associated with a second image of the atleast part of the real environment captured by the first camera at asecond pose relative to the second camera; and reconstructing a model ofthe at least part of the real environment according to the imageinformation associated with the first and second images and the firstand second poses.
 5. The method according to claim 4, further comprisingreceiving image information associated with a further image of at leastpart of the displayed visual content captured by the second camera whilethe first camera is at the second pose relative to the second camera;and determining the second pose of the first camera relative to thesecond camera according to the image information associated with thefurther image and the spatial relationship between the displayed visualcontent and the first camera.
 6. The method according to claim 1,wherein the pose of the first camera is relative to a real object, andwherein the determining the pose of the first camera comprises receivingimage information associated with an image of at least part of the realobject captured by the second camera, determining a homography accordingto image positions of the at least part of the displayed visual contentin the image of at least part of the displayed visual content and imagepositions of the at least part of the real object in the image of atleast part of the real object, wherein the at least part of thedisplayed visual content is planar and the at least part of the realobject is planar, and determining the pose of the first camera relativeto the real object according to the homography and the spatialrelationship.
 7. The method according to claim 1, wherein the pose ofthe first camera is a pose of the first camera at a first position whilethe image is captured relative to the first camera at a second position,and wherein the determining the pose of the first camera comprisesreceiving image information associated with a further image of at leastpart of the displayed visual content captured by the second camera whilethe first camera is at the second position, determining a homographyaccording to image positions of the at least part of the displayedvisual content in the image and in the further image, wherein the atleast part of the displayed visual content is planar, and determiningthe pose of the first camera according to the homography and the spatialrelationship.
 8. The method according to claim 7, further comprisingreceiving image information associated with a first image of at leastpart of a real environment captured by the first camera at the firstposition, receiving image information associated with a second image ofat least part of the real environment captured by the first camera atthe second position, and reconstructing a model of the at least part ofthe real environment according to the image information associated withthe first and second images and the pose of the first camera. 9.(canceled)
 10. The method according to claim 1, wherein the first cameraand the display device are physically connected.
 11. The methodaccording to claim 1, wherein the first camera is at a fixed positionwith respect to the display device after the spatial relationship isprovided.
 12. The method according to claim 1, wherein the first cameraand the display device are comprised in a mobile device.
 13. The methodaccording to claim 1, wherein the spatial relationship between thedisplayed visual content and the first camera is determined by ahand-eye calibration.
 14. (canceled)
 15. (canceled)
 16. A system fordetermining a pose of a first camera, comprising a processing deviceconfigured to provide or receive a spatial relationship between a visualcontent displayed on a display device and the first camera; theprocessing device configured to receive image information associatedwith an image of at least part of the displayed visual content capturedby a second camera; the processing device configured to determine a poseof the first camera according to the image information associated withthe image and the spatial relationship.
 17. The system according toclaim 16, wherein the processing device is comprised in a mobile devicewhich comprises the first camera.
 18. The system according to claim 16,wherein the processing device is comprised in a mobile device whichcomprises the second camera.
 19. The system according to claim 16,wherein the processing device is comprised in a computer device whichcommunicates with a first mobile device comprising the first camera anda second mobile device comprising the second camera.
 20. The systemaccording to claim 16, wherein the first camera and the display deviceare comprised in a mobile device.
 21. (canceled)
 22. The systemaccording to claim 16, wherein the second camera is comprised in amobile device, particularly a head mounted display device. 23.(canceled)
 24. A computer readable medium comprising computer readablecode which, when executed by one or more processors, causes the one ormore processors to: obtain a spatial relationship between a visualcontent displayed on a display device and the first camera, receiveimage information associated with an image of at least part of thedisplayed visual content captured by a second camera, and determining apose of the first camera according to the image information associatedwith the image and the spatial relationship.
 25. The computer readablemedium of claim 24, wherein the pose of the first camera is a pose ofthe first camera relative to the second camera, and wherein thedetermining the pose of the first camera comprises determining a pose ofthe second camera relative to the displayed visual content according tothe image information associated with the image.